Correlation Decay up to Uniqueness in Spin Systems Yitong Yin - - PowerPoint PPT Presentation

correlation decay up to uniqueness in spin systems
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Correlation Decay up to Uniqueness in Spin Systems Yitong Yin - - PowerPoint PPT Presentation

Correlation Decay up to Uniqueness in Spin Systems Yitong Yin Nanjing University Joint work with Liang Li ( Peking University ) Pinyan Lu ( Microsoft research Asia ) Two-State Spin System 2 states {0,1} graph G =( V , E ) configuration : V


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SLIDE 1

Correlation Decay up to Uniqueness in Spin Systems

Joint work with Liang Li (Peking University) Pinyan Lu (Microsoft research Asia) Yitong Yin Nanjing University

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SLIDE 2

Two-State Spin System

A = A0,0 A0,1 A1,0 A1,1

  • =

β 1 1 γ

  • 2 states {0,1}

configuration σ : V → {0, 1} graph G=(V,E) edge activity:

β γ 1

external field:

1 λ

b = (b0, b1) = (λ, 1)

w(σ) =

  • (u,v)∈E

Aσ(u),σ(v)

  • v∈V

bσ(v)

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SLIDE 3

Two-State Spin System

A = A0,0 A0,1 A1,0 A1,1

  • =

β 1 1 γ

  • 2 states {0,1}

configuration σ : V → {0, 1} graph G=(V,E)

w(σ) =

  • (u,v)∈E

Aσ(u),σ(v)

  • v∈V

bσ(v)

Gibbs measure:

=

  • σ∈{0,1}V

w(σ)

partition function:

Z(G)

(σ) = w(σ) Z(G)

b = (b0, b1) = (λ, 1)

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SLIDE 4

w(σ) =

  • (u,v)∈E

Aσ(u),σ(v)

  • v∈V

bσ(v)

marginal probability:

1/n additive error for marginal in poly(n)-time FPTAS for Z(G)

Gibbs measure:

(σ) = w(σ) Z(G)

=

  • σ∈{0,1}V

Z(G) w(σ)

partition function:

(σ(v) = 0 | σΛ)

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SLIDE 5

ferromagnetic:

[Jerrum-Sinclair’93]

βγ > 1

FPRAS:

[Goldberg-Jerrum-Paterson’03]

anti-ferromagnetic:

βγ < 1

hardcore model: Ising model:

β = 0, γ = 1 β = γ

∃ FPTAS for graphs

  • f max-degree Δ

(β, γ, λ) lies in the interior of uniqueness region of Δ-regular tree [Sinclair-Srivastava-Thurley’12] [Weitz’06]

0.5 1 1.5 2 2.5 3 0.5 1 1.5 2 2.5 3

  • 0< , <1

= 1

uniqueness threshold threshold achieved by heatbath random walk

β γ

[Li-Lu-Y. ’12]: FPTAS for arbitrary graphs [Goldberg-Jerrum-Paterson’03]

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SLIDE 6

anti-ferromagnetic:

βγ < 1

∃ FPTAS for graphs of max-degree Δ (β, γ, λ) lies in the interiors of uniqueness regions of d-regular trees for all d ≤ Δ. ∄ FPRAS for graphs of max-degree Δ

(β, γ, λ) lies in the interiors of non-uniqueness regions of d-regular trees for some d ≤ Δ.

assuming NP ≠RP

[Sly-Sun’12] [Galanis-Stefankovic-Vigoda’12]: bounded Δ or Δ=∞

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SLIDE 7

Uniqueness Condition

(d+1)-regular tree

reg. tree

t

arbitrary boundary config

marginal at root ± exp(-t) fd(x) = λ βx + 1 x + γ d

ˆ xd = fd(ˆ xd) |f

d(ˆ

xd)| < 1

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SLIDE 8

anti-ferromagnetic:

βγ < 1

∃ FPTAS for graphs of max-degree Δ ∄ FPRAS for graphs of max-degree Δ

assuming NP ≠RP

[Sly-Sun’12] [Galanis-Stefankovic-Vigoda’12]: bounded Δ or Δ=∞ ∀d < ∆, |f

d(ˆ

xd)| < 1 ∃d < ∆, |f

d(ˆ

xd)| > 1

fd(x) = λ βx + 1 x + γ d

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SLIDE 9

Correlation Decay

strong spatial mixing (SSM): B

∂B

G v

∀σ∂B, τ∂B ∈ {0, 1}∂B Λ

t weak spatial mixing (WSM): Uniqueness: WSM in reg. tree

| (σ(v) = 0 | σ∂B) − (σ(v) = 0 | τ∂B)| ≤ (−Ω(t)) | (σ(v) = 0 | σ∂B, σΛ) − (σ(v) = 0 | τ∂B, σΛ)| ≤ (−Ω(t))

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SLIDE 10

1

Self-Avoiding Walk Tree

due to Weitz (2006)

1 2 3 4 5 6 2 4 4 1 4 4 6 5 5 6 4 3 3 5 6 5 6 4 1

G=(V,E) v

T = T(G, v) 6 6 6 6 6 σΛ preserve the marginal dist. at v

SSM FPTAS

  • n bounded degree graphs:
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SLIDE 11

v T v1 v2 vd T1 Td x = f(x1, . . . , xd) = λ

d

  • i=1

βxi + 1 xi + γ

  • x = [σ(v) = 0 | σΛ]

[σ(v) = 1 | σΛ] x n ∈ [0, ∞) x ∈ [R, R + δ] δ = (−Ω(n))

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SLIDE 12

Potential Analysis

x f(x) f Fn(x + δ) − Fn(x) = F

n(x0) · δ

Fn(x) = f f · · · f

  • n

(x) = δ ·

n1

  • t=0

f (xt) xt = f(xt−1) = δ · Φ(x0) Φ(xn) ·

n1

  • t=0

Φ(f(xt)) Φ(xt) f (xt)

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SLIDE 13

Potential Analysis

x f(x) y g(y) g f φ φ−1 φ(x) = Φ(x) G

n(x0) = n1

  • t=0

g(xt) =

n1

  • t=0

[φ(f(φ1(yt))] =

n1

  • t=0

Φ(f(xt)) Φ(xt) f (xt) Gn(x) = g g · · · g

  • n

(x) Gn(x + δ) − Gn(x) = G

n(x0) · δ

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SLIDE 14

v v1 v2 vd x1 xd x v v1 v2 vd y y1 yd φ

f(x1, . . . , xd) = λ

d

  • i=1

βxi + 1 xi + γ

  • g(y1, . . . , yd) g(y1 + δ1, . . . , yd + δd)

= φ(f(φ−1(y1), . . . , φ−1(yd))) · (δ1, . . . , δd)

φ(x) = Φ(x) = 1

  • x(βx + 1)(x + γ)

≤ α(d; x1, . . . , xd) ·

1≤i≤d{δi}

+δ1 +δd

amortized decay rate

g(y1, . . . , yd) = φ(f(φ−1(y1), . . . , φ−1(yd)))

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SLIDE 15

α(d; x1, , xd) αd(x) α(d; x, . . . , x

d

)

Convexity analysis

amortized decay rate

= Φ(f(x)) Φ(x) |f (x)|

= (1 − βγ)

  • λ d

i=1 βxi+1 xi+γ

1

2

  • βλ d

i=1 βxi+1 xi+γ + 1

1

2

λ d

i=1 βxi+1 xi+γ + γ

1

2 ·

d

  • i=1

x

1 2

i

(βxi + 1)

1 2 (xi + γ) 1 2

=

  • d(1 − βγ)x

(βx + 1)(x + γ)

  • d(1 − βγ)λ
  • βx+1

x+γ

d

  • βλ
  • βx+1

x+γ

d + 1 λ

  • βx+1

x+γ

d + γ

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SLIDE 16

αd(x)

=

  • d(1 − βγ)x

(βx + 1)(x + γ)

  • d(1 − βγ)λ
  • βx+1

x+γ

d

  • βλ
  • βx+1

x+γ

d + 1 λ

  • βx+1

x+γ

d + γ

  • fd(x) = λ

βx + 1 x + γ d

ˆ xd = fd(ˆ xd) |f

d(ˆ

xd)| < 1

  • d(1 − βγ)ˆ

x (βˆ x + 1)(ˆ x + γ) =

  • |f

d(ˆ

xd)|

=

  • d(1 − βγ)x

(βx + 1)(x + γ)

  • d(1 − βγ)fd(x)

(βfd(x) + 1) (fd(x) + γ)

v v1 v2 vd y y1 yd +δ1 +δd +δ

δ ≤ α ·

1≤i≤d{δi}

α < 1

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SLIDE 17

anti-ferromagnetic:

βγ < 1 ∃ FPTAS for graphs of max-degree Δ ∀d < ∆, |f

d(ˆ

xd)| < 1

fd(x) = λ βx + 1 x + γ d

SSM in graphs of max-degree Δ SSM in trees of max-degree Δ bounded Δ

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SLIDE 18

Computationally Efficient Correlation Decay

for some

αd(x) =

  • d(1 − βγ)x

(βx + 1)(x + γ)

  • d(1 − βγ)fd(x)

(βfd(x) + 1) (fd(x) + γ)

v v1 v2 vd y y1 yd +δ1 +δd +δ δ ≤ αd(x) ·

1≤i≤d{δi}

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SLIDE 19

Computationally Efficient Correlation Decay

for some

for small

  • ne-step recursion decays

for large

  • ne-step recursion decays

behaves like steps!

αd(x) v v1 v2 vd y y1 yd +δ1 +δd +δ δ ≤ αd(x) ·

1≤i≤d{δi}

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SLIDE 20

anti-ferromagnetic:

βγ < 1 ∃ FPTAS for graphs of max-degree Δ bounded Δ or Δ=∞ WSM in d-reg. trees for d ≤ Δ

hardcore model Ising model

[Sinclair-Srivastava-Thurley’12] [Weitz’06] [Li-Lu-Y. ’12] unbounded-degree graphs, no external field

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SLIDE 21

Open Problems

  • Characterization of SSM in ferromagnetic 2-state spin

systems.

  • SSM in multi-state spin systems:
  • difficulty: no SAW-tree;
  • implications: WSM vs. SSM in reg. trees, monotonicity of

WSM/SSM w.r.t degree.

  • Apply potential analysis and computationally efficient

correlation decay to other problems.

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SLIDE 22

Thank you! (again)